Gordon Bell has been involved with self-tracking for over a decade. From his ground-breakign MyLifeBits project to his popular book on the possibilities of a fully digital life he is constantly thinking about new ways we can understand ourselves through the data we collect. We are always excited to see him at our QS events and were especially happy to have him reach out to us about presenting at our last Bay Area QS meetup.

Gordon Bell’s HR data from a day he visited with his lawyers. Note the spike during the meeting in the morning.

Gordon has experienced two heart attacks, one in 1983 and another in 1996, two double bypasses, and currently is living with his third pacemaker. It probably isn’t surprising given his medical history that he has a keen interest in understanding his heart. In this talk Gordon describes what he’s been learning from the data collected from his pacemaker and the 320 days of heart rate and activity data he has collected with his Basis watch.

We’re also excited to have Gordon joining us at our upcoming QS15 Conference & Activate Expo. We’ve made some early bird tickets available for readers of the Quantified Self blog (for a limited time): Register here!

There will be eight great Quantified Self meetups happening all over the world this week. The group in Stockholm will have show&tell talks on sleep tracking, using the Scanadu Scout and using personal data to identify cause and effect in one’s life. Our exemplary QSXX Boston group will be getting together as well. To learn more on how the QSXX meetup groups create a safe space for discussing women-centric self-tracking topics, click here.

To see when the next meetup in your area is, check the full list of the over 100 QS meetup groups in the right sidebar. Don’t see one near you? Why not start your own! If you organize a QS meetup, please post pictures of your event to the Meetup website. We love seeing them.

After the Data Confessional: interview with Ellie Harrison by Stephen Fortune. A very interesting and thought-provoking interview with artist Ellie Harrison. For six years self-tracking data was the core component of Ellie’s work as an artist. Then she decided to stop and reconsider her tracking practices and what it meant to her and her work.

Data is the New “___” by Sara M. Watson. “What do we talk about when we talk about data?” is the question Sara posses here to frame a wonderful piece on how our use of metaphors influences our view of data.

Baby Lucent: Pitfalls of Applying Quantified Self to Baby Products [PDF] by Kevin Gaunt, Júlia Nacsa, and Marcel Penz. An interesting article here from three Swedish design students that looks at current baby and parenting tracking technology. They also conducted a design process to develop a future tracking concept to better understand parent’s reactions to baby tracking. I thought there were a few interesting finding from their interviews.

Hey, Nate: There Is No ‘Rich Data’ In Women’s Sports by Allison McCann. It only seems fitting that a few days before this weekend’s MIT Sloan Conference on Sports Analytics Conference, the “it” place to learn about and discuss sports data, that we learn about the amazing dearth of data collected and published about women’s sports.

Show&TellAnalyzing Email Data by Austin G. Waters. A great deep dive into the 23,965 emails that Austin has collected in his personal account since 2009. I won’t spoil it, but this post just keeps getting better and better as you scroll. Bonus points to Austin for describing his methods and open-sourcing the code he used to conduct this analysis.

Smart Art by Natasha Dzurny. Using IFTTT and a few littleBits modules Natasha created a piece of artwork that reflects how often she goes to the gym. Would love to seem more DIY data reflections like this!

How does weather affect U.S. sleep patterns? by Sleep Cycle. Sleep Cycle analyzed 142,272 sleep reports from their users (recorded in January of 2015) to explore mood upon awakening, stress levels before bed, and sleep quality. Fascinating stuff.

Greg Kroleski has been tracking his time for the past six years, starting when he was 20-years old. Using a spreadsheet he designed himself he collects how much time he spends in eight different categories: Survival, Labor, Social, Spiritual, Mind, Expression, Body, and Distraction. In this talk, presented at the San Francisco QS meetup group, Greg describes the data he’s collected and what he’s learned about where his time goes. If you’re interested in applying his tracking methodology he’s graciously put his spreadsheet template online here.

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In our Access Channel we’re trying to expose ideas, efforts, and insights about personal data access and it’s role in both generating personal and public insights. The last time we wrote about data donation we mentioned a few different projects that allowed you to collect and/or publish your self-tracking data for others to view and access. Today we’re going to showcase a few research-focused projects that collect personal data, but also allow participants to access the data they contribute. This seemingly minor addition, participant access to data, is actually a process not commonly employed by research studies. We’re very interested in new participatory models of research that respect participant’s rights to fully understand and access the data they contribute. If you know of others please get in touch and we’ll add them to the list.

Personal Genome Project: Harvard
Probably the most well-known of these research projects is the ongoing Personal Genomes Project based at Harvard University (PGP). Led by George Church and an outstanding team, the PGP is an ongoing research project recruiting participants to “share their genetic, health, and trait data in a public and non-anonymous manner. Participation is free.

American Gut
Much like the project above, the American Gut project is an open call for participant to collect and share their data. In this case it is human microbiome data. Although enrollment is not free (they request donations starting at $99 to participate) data is returned to participants. (If you’re interested in participating in microbiome research, but live in Europe see the British Gut project)

Dynamics of the Human Microbiota
This new project, based out of Stanford, is also exploring the human microbiome. This study includes a variety of different perturbations and longitudinal data collection. Participants are compensated for their participation, their data is made accessible to them, and they have the opportunity to discuss their results with the study staff.

For those of you interested in research methods and ethics we recommend reading this brief article by Jeantine E. Lunshof, George M. Church, and Barbara Prainsack: Raw Personal Data: Providing Access

On June 18-20 we’ll be hosting the QS15 Conference & Activate Expo in San Francisco at the beautiful facilities at the Fort Mason Center. This will be a very special year with three days of inspiring talks, demos, and discussion with your fellow self-trackers and toolmakers. As we start to fill out our program we’ll be highlighting speakers, discussion leaders, sponsors, and attendees here.

Julie Price is a long time member of our Bay Area QS meetup group and will be attending the QS15 Conference & Activate Expo to share her self-tracking story. Julie has been using and experimenting with a wide range of self-tracking tools and behavioral techniques to understand herself. Previously she’s shared her experiences using commercial tools and self-designed methods to understand and improve her marathon training.

Over the past 4 years, Julie has tracked her weight as it moved within a 30 pound range, varying wildly within each year. In December, Julie shared the factors that influenced her weight the most: family visits, distance road races, and a variety of weight loss tactics. As part of our show&tell program, Julie will share an update that includes her newest insights into her weight fluctuations as well as what interventions have made the greatest impact on her weight.

We’re excited to have Julie joining us and asked her a few questions about herself and what she’s looking forward to at the conference.

Julie: Hands-down, I love the Whistle to measure my dog’s activity. I use Basis Peak and my husband uses Jawbone Up. Both seem well-designed for certain scenarios and not for others. Between all the wearables we’ve tried, the Whistle has been the most successful in influencing our behavior.

QS: What are you most looking forward to at the conference?

Julie: I’m looking forward to meeting interesting people, learning from their stories, and learning from their creative experiments and observations. But, I’m most looking forward to exploring new ideas that impact the behavior of people who don’t necessarily enjoy data.

QS: What should people come talk to you about at the conference?

Julie: I’m an expert in UX, interaction design, usability, health behavior change, and fitness. I’d love to talk about creative tactics for eliciting behavior change and a process for ensuring the right product and experience is designed for the right person. I also love to talk about health gaming and the complexities of the space.

QS: What tools, devices, or apps do you want to see at the conference?

Julie: Any product in health and fitness that is truly different or thought through from the perspective of the user. I’d love to see any product built with a process that continually validates their direction with target users.

QS: What topic do you think that Quantified Self community is not talking enough about?

Julie: We should explore more innovative ways to meet people where they are and creatively influence them gradually in a way that is meaningful and lasting. It would be great to talk more about what progressive techniques could be applied in order to create impact over both short and long periods of time.

Julie’s session is just one of the many hands-on, up-to-date, expertly moderated sessions we’re planning for the QS15 Global Conference and Exposition. We’ve made some early bird tickets available for readers of the Quantified Self blog (for a limited time): Register here!

This week will bring four fascinating Quantified Self meetups. St. Louis will have a “quantified romance”-themed meetup including a toolmaker talk with the creator of a service that helps with romantic decisions. In Ashland, they will be getting together to discuss n=1 study designs. This is the same group that started the Individual Metabolic Research Group (iMeRG) that we featured a couple of days ago.

To see when the next meetup in your area is, check the full list of the over 100 QS meetup groups in the right sidebar. Don’t see one near you? Why not start your own! If you organize a QS meetup, please post pictures of your event to the Meetup website. We love seeing them.

ArticlesThe Wow of Wearables by Joseph Kvedar. An excellent post here in the wake of the “Smartphones vs. Wearables” hype in the past weeks. Favorite part:

“I’d have to say that reports of the death of wearables have been greatly exaggerated. The power of sensor-generated data in personal health and chronic illness management is simply too powerful to ignore.”

A Few Throughs About Patient Health Data by Emil Chiauzzi. Emil, Research Director at PatientsLikeMe, lays out four point to consider when thinking about how to best use and grow self-collected patient data.

I am the only person with the whole picture. To me, self-care is everything I do to stay as healthy as possible with a disease that is a difficult life companion. It entails everything from making sure I take my medication in the optimal way, to eating healthily, getting enough sleep, to making sure I stay physically active. I also make an effort to learn as much as I can about my condition; my neurologist says that I know more about Parkinson’s research than he does. I don’t find that odd, since he needs to try to stay on top of research in probably hundreds of neurological diseases, whereas I focus on just one.

Here at QS Labs we take great pride in supporting a worldwide network of meetup groups. From Bucharest to the Bay Area, we have over 100 groups meeting to discuss self-tracking, share experiences, and learn from each other.

We wanted to highlight a new group, based in southern Oregon, that is using self-tracking to expand and influence medical knowledge within the healthcare system. Dr. Dawn Lemanne, a board certified and practicing oncologist, has started the new Individual Metabolic Research Group (iMeRG) to develop, test, and explore inexpensive way to prevent and treat chronic diseases related to lifestyle, through rigorous N of 1 research methods.

Currently the iMERG is a composed of physicians and other health care professionals frustrated by the rising rates of lifestyle driven chronic disease, and the failure of the large randomized controlled trial (RCT) to provide effective interventions. Inspired by QS, they are working together to develop and use rigorous N of 1 research designs, while using themselves (not their patients) as subjects. Members propose projects, and together they figure out how to do it. QS devices and philosophies play a major role in the data collection and analysis methods being talked about at the group. Current proposals have included:

How best to measure the effect of combining intermittent fasting and exercise on blood ketone levels and inflammatory markers in a sedentary postmenopausal woman

Join the group! If you hold a license to practice a health profession (MD, DO, DDS, DMD, RN, NP, PA, DC, ND, LAc, etc.), you’re interested in N of 1 research design and methods, and you’d like to be involved, please contact Dawn. All individuals are welcome, regardless of geographic location. If you’re in the southern Oregon area you can join their meetup group on February 28th. We’ll be posting updates from the group as their research progresses.

Dana Lewis and Scott Leibrand are the creators of the amazing “Do-It-Yourself-Pancreas-System,” also known by #DIYPS. We had a few question for them.

Ernesto: Why build your own pancreas?

Dana:

I’ve had Type 1 diabetes for about 12 years. I use an insulin pump and a continuous glucose monitor (CGM), but the devices are separate. They don’t talk to each other. I have to look at the data from the CGM and then make decisions about my insulin. I have to make about 300 decisions per day on average. It’s really fatiguing. So we created some algorithms that took my blood glucose data, the amount of insulin that I’ve given myself, and the amount of carbohydrates that I’ve decided that I’ve eaten, and ran them over and over again to give me a prediction of what my blood sugar was going to be and whether I need to take any action. Instead of having to constantly do the math myself, our system will push an alert to my phone or watch.

Dana: Originally no, but more recently we’ve built a full closed loop version of #DIYPS, that is essentially an artificial pancreas, that talks to my pump and adjusts to give me a little more or a little less insulin.

Ernesto: Who writes the code?

Scott: I’m doing all the coding. I’m sure Dana could, but she has a lot going on and designs the algorithms. My title is Chief Spaghetti-Coder. This is the bleeding edge. It doesn’t need to be elegant code.

Ernesto: What have you learned from building your own pancreas?

Dana: The beauty of a CGM is that it gives you a data point every five minutes. Over the past year I’ve produced more than 130,000 data points of blood sugar levels alone. That gives me an incredible picture of what’s happening. With a traditional meter, it’s rare to find somebody who tests up to even 10 times a day. And the standard use for an insulin pump is very much “set it and forget it.” The #DIYPS allows me to customize without having to constantly adjust my insulin pump manually, and that frees me up to live my life, work, and do whatever it is that I want to do.

A visualization of Dana’s Data over the first year of the #DIYPS system.

Ernesto: How did this project start?

Dana: We first started building the system just to make the alarms on the device louder, to wake me up because I would sleep through them. The device manufacturers didn’t seem to have a solution. Then we started looking at getting the data onto a computer so Scott would be able to view it. At the time, we had recently started dating, and he lives 20 miles away. I wanted him to be able to see what my blood glucose level was, so if it was low, he could text me; and if I didn’t respond, he could call 911. But we didn’t have a way to get the data off of the device.

Scott: The key moment was when we saw a tweet from John Costik, who was working on the Nightscout Project. Nightscout is open source code that helps people transmit their CGM data to other devices. I tweeted John right away: “Hey it would be awesome if we could get access to this code.” That’s really where it started. And along the way the whole process has been extremely public. We’ve been tweeting, blogging, and making everything we’ve been doing completely visible.

Ernesto: I’ve seen you tweet using the hashtag #wearenotwaiting. What does that mean?

Dana: #WeAreNotWaiting is a hashtag that was coined at a conference hosted by an online diabetes advocacy and information sharing community called DiabetesMine.com. For me it means that we’re not waiting for traditional device manufacturers to come out with the product. In three to ten years there’ll be devices like our artificial pancreas systems out in the market, being sold by companies approved by the FDA. I need to be alive when that system gets out in the market in, perhaps, five years.

I need to be alive when a cure becomes available.

Scott: Right about the time that we started working on #DIYPS, the Nightscout Project started to grow really quickly. There are now over 10,000 people in the CGM in the Cloud group. Over 2,000 people are using Nightscout to view their own or their loved ones’ blood sugar levels remotely on phones, watches, and other devices. This is real stuff that’s making a real difference in the world. And that’s only going to accelerate as more people do more interesting things like this closed loop that we’ve just done.

Ernesto: You’ve written about “data as free speech.” What do you mean? How can data be speech?

Dana: People often don’t understand why its legal for us to ‘hack’ a CGM and an insulin pump. (Note that hacking isn’t a negative thing; we’re just sharing the data across devices!) They assume that because all my DIY gadgets are not FDA-approved to use them the way I’m using them is somehow against the rules. But I can treat my own body, my own diabetes, the way I want to. And if I share my data, that’s obviously a kind of speech. But if we decide to share our code? I think the FDA sees this as a gray area. We very much want to continue our conversations with regulators.

Ernesto: Where do you see your project going?

Dana: I feel that every time I answer this question my answer changes, because my understanding of its potential is constantly changing. I never would have thought that any of what we’ve done was possible. Right now one of our goals is to make sure that the knowledge we gained about diabetes through our work with #DIYPS is adopted by clinicians, and that patients have access to this new information for treating diabetes. We’re also taking #DIYPS to a new level with #OpenAPS, an open and transparent effort to make safe and effective basic Artificial Pancreas System (APS) technology widely available to more quickly improve and save as many lives as possible and reduce the burden of Type 1 diabetes.

Dana with the #OpenAPS system.

Scott: A few of months ago, at a conference convened by the advocacy group DiabetesMine, we got up and talked about our project, and I said: “I’m putting a stake in the ground that we’re going to make a closed loop artificial pancreas by August 1st, which is the date we’re getting married.” Everybody applauded and thought that was awesome. Then we went home. And we had it done in two weeks.

Dana: For anybody who wants to get involved in this, we would love to talk to you. There are so many people with diabetes and there is so much data that drives the management of this disease.

But there’s not a lot of awareness of how manydiseases, including diabetes, could have their care revolutionized just by having better access to data.

That’s the thread of Quantified Self that I’m most interested in. The diabetes community happens to be one of the first to take advantage of what’s possible.

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